Modern hyper-converged distributed virtualization systems comprise components that coordinate to share sets of computing resources, data storage facilities, and networking facilities that are integrated into clusters. Such distributed systems have evolved in such a way that incremental linear scaling can be accomplished in many dimensions. Certain clusters in a distributed system might support over one hundred nodes that in turn support as many as several thousands (or more) autonomous computing-related entities. Such entities might be or be subsumed by virtual machines (VMs), application containers, storage devices, and/or other components in the distributed system. Metadata characterizing aspects of the entities can be implemented in the distributed system to manage the entities. For example, the metadata can be used to operate on the entities (e.g., create or configure a VM, etc.) and/or monitor certain aspects of the entities (e.g., changes, accesses, permissions, etc.). Various access points (e.g., management interface) in a distributed system can be provided to perform entity management (e.g., configuration, monitoring, analyzing, etc.). A virtualized controller on one of many nodes in a given cluster might be elected as the access point (e.g., as an elected leader) for managing the cluster entities. In this case, the elected virtualized controller will have permissions as owner to modify the entity metadata.
Unfortunately, legacy techniques for managing entity metadata present limitations at least as pertaining to efficiently and accurately managing cross-cluster entities in a multi-cluster distributed environment. Legacy approaches that use access points at each cluster can introduce metastability of data or corruption of data when transitioning (e.g., scaling) from a single cluster implementation to a multi-cluster implementation. For example, in systems having multiple access points (e.g., at each cluster) legacy approaches can introduce inconsistencies (e.g., conflicts, inaccuracies, etc.) in the metadata for entities that have cross-cluster associations. Certain other legacy approaches might implement a single centralized access point for the multi-cluster system while disabling all other access points. Such approaches are inefficient, at least inasmuch as during the timeframe that all other access points are disabled, progress may be halted. Further, legacy approaches fail to consider certain physical variables or constraints (e.g., geographic distances or boundaries), and also fail to consider policy restrictions (e.g., cross-cluster restrictions), performance variables (e.g., latency), and/or other constraints when managing entities that are shared across two or more clusters.
What is needed is a technique or techniques to improve over legacy techniques and/or over other considered approaches. Some of the approaches described in this background section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.